The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to embodiments of the claimed inventions.
A single a multi-tenant database system operates to store data on behalf of a multitude of paying subscribers, each being a “tenant” of the database system, hence the term multi-tenant database system.
Within such an operational environment, computational efficiency, system responsiveness, and data security are all of paramount concern both to the provider of the multi-tenant database system and to the subscribers or tenants of such a system.
Over the past many years as the technology has matured and become increasingly commonplace within the marketplace, the conventional techniques used to perform various cross-organizational processing tasks have been overwhelmed by evolving security concerns and by the increasing computational burden of an ever increasing quantity of data to be stored within such a multi-tenant database system on behalf of its subscribers.
For instance, conventionally available cross-organizational processing techniques may not sufficiently accommodate stringent HIPAA (Health Insurance Portability and Accountability Act) protections enacted to secure private health care data for individuals due to a lack of abstraction of metrics and other metadata for such data. Similar concerns exist with other sensitive data, regardless of whether such data is specifically protected by Federal law. Further still, conventionally available cross-organizational processing techniques have failed to scale to multi-tenant database systems over a certain size and eventually reach an unacceptable state of perpetual processing burden in which pending and newly incoming processing demands outstrip processing capacity, resulting in workload that never completes, may be terminated or time-out, which may result in erroneously processed data records, non-processed data records, locked data records, and other problems familiar to those in the database arts.
The present state of the art may therefore benefit from the systems, methods, and apparatuses for implementing cross-organizational processing of business intelligence metrics as described herein.